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Thesis Defence: A Multilevel Meta-Analysis of Hemispatial Neglect Assessment Measures
July 26 at 11:00 am - 2:00 pm
Jason Scott, supervised by Dr. Maya Libben and Dr. Jamie Piercy, will defend their thesis titled “A Multilevel Meta-Analysis of Hemispatial Neglect Assessment Measures” in partial fulfillment of the requirements for the degree of Master of Science in Psychology.
An abstract for Jason Scott’s thesis is included below.
Defences are open to all members of the campus community as well as the general public. Registration is not required for in person defences.
Hemispatial neglect (HN) is a complex cognitive syndrome that is difficult to directly assess and rehabilitate (Verdon et al., 2010; Vuilleumier & Saj, 2013). As the leading cause of disability in stroke survivors, HN is a significant predictor of functional outcome, recovery trajectory, and hospital discharge status (Chen et al., 2015). Historically, the diagnosis of HN has incorporated “pencil-and-paper” assessment measures (Bickerton et al., 2011) that lack adequate sensitivity (Azouvi et al., 2002). Discouragingly, even the most effective measures, such as the Star Cancellation Test and the Line Bisection Test, show only modest sensitivity in identifying HN, with rates of 52% and 38% respectively (Lindell et al., 2007). In this study, we sought to assess the overall effectiveness of available specialized measures of HN using a multilevel meta-analytic approach. Results revealed that assessment measures of HN are sensitive in discerning visuospatial attentional impairments among populations with moderate to severe HN presentations and populations without HN. However, our findings suggest that the effectiveness of these measures in detecting true pathological performance may be better explained by characteristics other than the assessment measures themselves, such as the average time since initial injury, individuals’ age, stroke location, and the test scoring metric used. Without accounting for these influential factors, performance differences between these groups may show considerably smaller effects. Additionally, our findings suggest that certain measures may be more effective than others in their diagnostic accuracy. As such, this study provides valuable insights into the specific factors and measures that are necessary to better understand test performance differences between groups with HN and groups without HN. Accounting for these factors when measuring test performance in stroke populations may improve the diagnostic confidence and the appraisal of visuospatial deficits during clinical assessment, ultimately leading to better detection and intervention strategies for those with HN.